S. Umesh

1.3k citations
111 papers · 878 · h-index 17

Impact in

    • Speech and Audio Processing
    • Music and Audio Processing
    • Blind Source Separation Techniques
    • Speech Recognition and Synthesis
    • Natural Language Processing Techniques

Papers in

    • Speech Recognition and Synthesis 86
    • Natural Language Processing Techniques 10
    • Speech and dialogue systems 8
    • Speech and Audio Processing 78
    • Music and Audio Processing 58

S. Umesh

100 papers receiving 796 citations

Peers

S. Umesh
Comparison fields: 5 of 75
  • Signal Processing 595
  • Artificial Intelligence 631
  • Experimental and Cognitive Psychology 85
  • Developmental Biology 14
  • Computer Vision and Pattern Recognition 82
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Citations per field
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Citations per year

Countries citing papers authored by S. Umesh

Since Specialization
Citations

This map shows the geographic impact of S. Umesh's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by S. Umesh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Umesh more than expected).

Fields of papers citing papers by S. Umesh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. Umesh. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by S. Umesh. The network helps show where S. Umesh may publish in the future.

Co-authors

The 25 scholars most cited alongside S. Umesh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with S. Umesh Line = papers co-authored together S. Umesh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 111 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199650
2 201548
3 199948
4 201845
5 199943
6 201335
7 200429
8 200224
9 202124
10 200523
11 199323
12 200721
13
The development of the Cambridge University RT-04 diarisation system
200420
14 201320
15 200819
16 200216
17 200216
18 200216
19 201915
20 201815

About S. Umesh

S. Umesh is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Physiology, having authored 111 papers that have together received 878 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (86 papers), Speech and Audio Processing (78 papers), Music and Audio Processing (58 papers), Natural Language Processing Techniques (10 papers), Speech and dialogue systems (8 papers), Advanced Data Compression Techniques (7 papers), Phonetics and Phonology Research (6 papers) and Voice and Speech Disorders (6 papers). The work is most often cited by research in Signal Processing (595 citations), Artificial Intelligence (631 citations), Experimental and Cognitive Psychology (85 citations), Developmental Biology (14 citations) and Computer Vision and Pattern Recognition (82 citations). S. Umesh has collaborated with scholars based in India, United States and Canada. Frequent co-authors include D.J. Nelson, Leon Cohen, D.W. Tufts, Rohit Sinha, K. Sivakumar, Nitin Prasad, Shakti P. Rath, Achintya Kumar Sarkar, Mark Gales and Hermann Ney. Their work appears in journals such as Speech Communication, IEEE Transactions on Audio Speech and Language Processing, IEEE/ACM Transactions on Audio Speech and Language Processing, IEEE Journal of Oceanic Engineering and IEEE Journal of Selected Topics in Signal Processing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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